The many different techniques for maximum power point tracking of photovoltaic (PV) arrays are discussed. The techniques are taken from the literature dating back to the earliest methods. It is shown that at least 19 distinct methods have been introduced in the literature, with many variations on implementation. This paper should serve as a convenient reference for future work in PV power generation.

/pdf/comparison-of-photovoltaic-array-maximum-power-point-2nci76j6n4.pdf

Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques

This paper presents evaluations among the most usual maximum power point tracking (MPPT) techniques, doing meaningful comparisons with respect to the amount of energy extracted from the photovoltaic (PV) panel [tracking factor (TF)] in relation to the available power, PV voltage ripple, dynamic response, and use of sensors. Using MatLab/Simulink and dSPACE platforms, a digitally controlled boost dc-dc converter was implemented and connected to an Agilent Solar Array E4350B simulator in order to verify the analytical procedures. The main experimental results are presented for conventional MPPT algorithms and improved MPPT algorithms named IC based on proportional-integral (PI) and perturb and observe based on PI. Moreover, the dynamic response and the TF are also evaluated using a user-friendly interface, which is capable of online program power profiles and computes the TF. Finally, a typical daily insulation is used in order to verify the experimental results for the main PV MPPT methods.

Evaluation of the Main MPPT Techniques for Photovoltaic Applications

Maximum power point (MPP) tracking (MPPT) techniques are widely applied in photovoltaic (PV) systems to make PV array generate peak power which depends on solar irradiation. Among all the MPPT strategies, the incremental-conductance (INC) algorithm is widely employed due to easy implementation and high tracking accuracy. In this paper, a novel variable step-size incremental-resistance MPPT algorithm is introduced, which not only has the merits of INC but also automatically adjusts the step size to track the PV array MPP. Compared with the variable step-size INC method, the proposed scheme can greatly improve the MPPT response speed and accuracy at steady state simultaneously. Moreover, it is more suitable for practical operating conditions due to a wider operating range. This paper provides the theoretical analysis and the design principle of the proposed MPPT strategy. Simulation and experimental results verify its feasibility.

A Novel Improved Variable Step-Size Incremental-Resistance MPPT Method for PV Systems

In recent years there has been a growing attention towards use of solar energy. The main advantages of photovoltaic (PV) systems employed for harnessing solar energy are lack of greenhouse gas emission, low maintenance costs, fewer limitations with regard to site of installation and absence of mechanical noise arising from moving parts. However, PV systems suffer from relatively low conversion efficiency. Therefore, maximum power point tracking (MPPT) for the solar array is essential in a PV system. The nonlinear behavior of PV systems as well as variations of the maximum power point with solar irradiance level and temperature complicates the tracking of the maximum power point. A variety of MPPT methods have been proposed and implemented. This review paper introduces a classification scheme for MPPT methods based on three categories: offline, online and hybrid methods. This classification, which can provide a convenient reference for future work in PV power generation, is based on the manner in which the control signal is generated and the PV power system behavior as it approaches steady state conditions. Some of the methods from each class are simulated in Matlab/Simulink environment in order to compare their performance. Furthermore, different MPPT methods are discussed in terms of the dynamic response of the PV system to variations in temperature and irradiance, attainable efficiency, and implementation considerations.

Classification and comparison of maximum power point tracking techniques for photovoltaic system: A review

Some uncertainties, such as the uncertain output power of a plug-in electric vehicle (PEV) due to its stochastic charging and discharging schedule, that of a wind generation unit due to the stochastic wind speed, and that of a solar generating source due to the stochastic illumination intensity, volatile fuel prices, and future uncertain load growth could lead to some risks in determining the optimal siting and sizing of distributed generators (DGs) in distribution system planning. Given this background, under the chance constrained programming (CCP) framework, a new method is presented to handle these uncertainties in the optimal siting and sizing of DGs. First, a mathematical model of CCP is developed with the minimization of the DGs' investment cost, operating cost, maintenance cost, network loss cost, as well as the capacity adequacy cost as the objective, security limitations as constraints, and the siting and sizing of DGs as optimization variables. Then, a Monte Carlo simulation-embedded genetic-algorithm-based approach is employed to solve the developed CCP model. Finally, the IEEE 37-node test feeder is used to verify the feasibility and effectiveness of the developed model and method, and the test results have demonstrated that the voltage profile and power-supply reliability for customers can be significantly improved and the network loss substantially reduced.

Optimal Siting and Sizing of Distributed Generators in Distribution Systems Considering Uncertainties

A new maximum-power-point-tracking (MPPT) method for a photovoltaic (PV) power generation system was studied which can efficiently generate PV power even under changing weather conditions. In order to research a method suitable for the actual photovoltaic power system, PV characteristics of the maximum power point were measured for more than six months using a PV curve tracer. The actual maximum power points vary with conditions such as the surface temperature and the quantity of solar radiation. So, relationships between the maximum power point and circuit variables such as open circuit voltage and short circuit current were examined under various conditions appearing in the PV power generation system. It was found through measurements that the relationship between the maximum power and the current that the output power was almost a linear function in the actual solar arrays, regardless of the weather conditions. The MPPT method was proposed based on the obtained findings. It was verified through simulations and experiments that the proposed method enables the solar arrays to quickly generate the maximum power as determined by weather conditions at the time.

T. Matuo

Papers

Prediction-data-based maximum-power-point-tracking method for photovoltaic power generation systems